(Springer, Tokyo, 2002) Pulasinghe, K; Watanabe, K; Kiguchi, K; Izumi, K
This paper investigates the credibility of voice (especially natural language commands) as a communication medium in sharing advanced sensory capacity and knowledge of the human with a robot to perform a cooperative task.
Identification of the machine sensitive words in the unconstrained speech signal and
interpretation of the imprecise natural language commands for the machine has
been considered. The system constituents include a hidden Markov model (HMM)
based continuous automatie speech recognizer (ASR) to identify the lexical content of the user's speech signal, a fuzzy neural network (FNN) to comprehend the
natural language (NL) contained in identified lexical content, an artificial neural
network (ANN) to activate the desired functional ability, and contral modules to
generate output signals to the actuators of the machine. The characteristic features
have been tested experimentally by utilizing them to navigate a Khepera® in real
time using the user's visual information transferred by speech signals
